ER2Net: an evidential reasoning rule–enabled neural network for reliable triple-negative breast cancer tumor segmentation in magnetic resonance imaging

Puntos clave

• Segmentation accuracy significantly improved, enhancing reliability for tumor detection.
• Key performance enhancements include better sensitivity, confidence calibration, and uncertainty estimation.
• Assessment using enhanced fusion techniques and an uncertainty metric was employed in the analysis.
• Highlights the potential for MRI-based tools to aid in personalized treatment for breast cancer patients.